September 10, 2018
<www.bibliometrix.org>
Export from Web of Science in Bibtex format!
Export from Web of Science in Bibtex format!
Load packages…
library("bibliometrix") # for biblio-analytics
library("tidyr") # for table manipulations
library("dplyr") # for table manipulations
library("plyr") # for table manipulations
library("tidyverse") # for graphics/table management
library("ggplot2") # for graphics
library("ggmap") # for graphics
library("RColorBrewer") # for graphics
library("tm") # text analysis for word clouds
library("SnowballC") # text analysis for word clouds
library("wordcloud") # text analysis for word clouds
Load bibtex file
bib.dir <- paste0("D:\\Vero\\Documents\\R\\R_ladies_presentations\\bibliometrix\\")
niche.bib <- readFiles(paste0(bib.dir,"niche_theory_484.bib"))
Convert
niche.df <- convert2df(niche.bib,dbsource = "isi", format = "bibtex")
Quick biblioanalysis
niche.biblio <- biblioAnalysis(niche.df, sep = ";")
Get summary
summary(niche.biblio, k=5, pause=FALSE) #k=5 is first 5 on list
Get summary
summary(niche.biblio, k=5, pause=FALSE) #k=5 is first 5 on list
Graphics
plot(x=niche.biblio, k=5, pause=FALSE)
art.yrs <- ddply(niche.df, .(PY), summarize, count=length(PY))
wordcloud(words=keyterms.df$word, freq=keyterms.df$freq,
min.freq=10, max.words=100, random.order=FALSE,
rot.per=0.0, colors=brewer.pal(8, "Paired"))
keyterms.df[grep("climate", keyterms.df$word),]
## word freq ## climate climate 156 ## climates climates 9 ## macroclimate macroclimate 3 ## paleoclimate paleoclimate 1
options(width=65) # ensure width findAssocs(term.mtrx1, terms = "climate", corlimit = 0.35)
## $climate ## change vulnerability phenological douglas ## 0.68 0.55 0.50 0.46 ## frost interior nitschke taca ## 0.46 0.46 0.46 0.46 ## columbia future respond phenology ## 0.41 0.38 0.38 0.38 ## merging pau photoperiod reponses ## 0.38 0.38 0.38 0.38 ## british climatic ## 0.37 0.35
Number of articles per country
Questions?
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twitter: @VFFRANS